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目的制备聚乳酸(PLLA)三维微小凹图式并实现图式上新生大鼠海马神经干细胞(NSC)三维聚集体的形成及培养。方法用2只新生1~3 d SPF级SD大鼠体外分离提取海马组织并培养NSC,观察其悬浮神经球和贴壁生长特性;以紫外光光刻和复制模塑法制备3种不同结构尺寸的PLLA微小凹图式;以普通光学显微镜和Image J图像处理软件研究图式上NSC聚集体的形成及大小分布;以免疫细胞荧光技术研究图式上NSC标志物Nestin的表达。结果 NSC在体外能够以悬浮神经球和贴壁生长的2种方式生长。在所研究的3种结构尺寸的图式中,无通道(120-0μm)和通道宽度为20μm(120-20μm)的微小凹图式更利于NSC聚集体的形成(P<0.01);而在通道宽度为40μm的图式(120-40μm)上NSC更倾向于沿通道方向生长、迁移,并形成准一维排布的三维神经细胞网络。图式上聚集体Feret’s直径分布均匀,无大的聚集体(直径>120μm)出现。在细胞聚集体及神经细胞网络形成期间NSC均保持Nestin阳性表达。结论 PLLA微小凹图式可用于体外NSC聚集体形成及神经细胞网络的三维图式化,这为干细胞组织工程及基于神经细胞的微系统提供了有效的研究及应用途径。
Objective To prepare three-dimensional microdisciplinary patterns of polylactic acid (PLLA) and to establish the formation and culture of three-dimensional aggregates of hippocampus neural stem cells (NSCs) in neonatal rats. Methods Two newborn SD rats of 1 ~ 3 d SPF grade were isolated from hippocampus and cultured in vitro to observe the growth characteristics of suspended neurospheres and adherent growth. Three different sizes of structures were prepared by ultraviolet photolithography and replication molding PLLA microgroove pattern. The formation and size distribution of the NSC aggregates on the graph were studied by using ordinary optical microscope and Image J image processing software. The expression of Nestin, a NSC marker, was studied by immunofluorescence technique. Results NSC could grow in 2 ways in vitro with neurospheres and adherent growth. Among the three structures studied, fine pits with no channel (120-0μm) and channel width of 20μm (120-20μm) were more favorable for the formation of NSC aggregates (P <0.01) The NSCs on the 40μm channel width (120-40μm) are more likely to grow and migrate in the channel direction and form a quasi-one dimensional network of three-dimensional neural cells. Schematic aggregate Feret’s diameter distribution, no large aggregates (diameter> 120μm) appear. Both NSCs maintained Nestin positive expression during cell aggregates and neural network formation. Conclusion The PLLA micro-concave pattern can be used for the formation of NSC aggregates in vitro and 3D patterning of neural network, which provides an effective research and application approach for stem cell tissue engineering and neural cell-based micro-systems.